Co-located with Supercomputing/SC 2011
Seattle Washington -- November 14th, 2011
Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements. Some applications generate data volumes reaching hundreds of terabytes and even petabytes. As scientific applications become more data intensive, the management of data resources and dataflow between the storage and compute resources is becoming the main bottleneck. Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the “fourth paradigm” in scientific discovery after theoretical, experimental, and computational science.
The second international workshop on Data-intensive Computing in the Clouds (DataCloud-SC11) will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running data-intensive computing workloads on Cloud Computing infrastructures. The DataCloud-SC11 workshop will focus on the use of cloud-based technologies to meet the new data intensive scientific challenges that are not well served by the current supercomputers, grids or compute-intensive clouds. We believe the workshop will be an excellent place to help the community define the current state, determine future goals, and present architectures and services for future clouds supporting data intensive computing.
For more information about the workshop, please see http://datasys.cs.iit.edu/events/DataCloud-SC11/. To see the 1st workshop's program agenda, and accepted papers and presentations, please see http://www.cse.buffalo.edu/faculty/tkosar/datacloud2011/. We are also running a Special Issue on Data Intensive Computing in the Clouds in the Springer Journal of Grid Computing with a paper submission deadline of August 16th 2011, which will appear in print in June 2012.
Authors are invited to submit papers with unpublished, original work of not more than 10 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per ACM 8.5 x 11 manuscript guidelines (http://www.acm.org/publications/instructions_for_proceedings_volumes); document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates. We are also seeking position papers of no more than 5 pages in length. A 250 word abstract (PDF format) must be submitted online at https://cmt.research.microsoft.com/DataCloud_SC11/ before the deadline of September 2nd, 2011 at 11:59PM PST; the final 5/10 page papers in PDF format will be due on September 9th, 2011 at 11:59PM PST. Papers will be peer-reviewed, and accepted papers will be published in the workshop proceedings as part of the ACM digital library (pending approval). Notifications of the paper decisions will be sent out by October 7th, 2011. Selected excellent work may be eligible for additional post-conference publication as journal articles. We are currently running a Special Issue on Data Intensive Computing in the Clouds in the Springer Journal of Grid Computing. Submission implies the willingness of at least one of the authors to register and present the paper. For more information, please see http://datasys.cs.iit.edu/events/DataCloud-SC11/ or send email to datacloud-sc11-chairs@xxxxxxxxxxxxxxxxxx.
General Chairs (datacloud-sc11-chairs@xxxxxxxxxxxxxxxxxx)
-- ================================================================= Ioan Raicu, Ph.D. Assistant Professor, Illinois Institute of Technology (IIT) Guest Research Faculty, Argonne National Laboratory (ANL) ================================================================= Data-Intensive Distributed Systems Laboratory, CS/IIT Distributed Systems Laboratory, MCS/ANL ================================================================= Cel: 1-847-722-0876 Office: 1-312-567-5704 Email: iraicu@xxxxxxxxxx Web: http://www.cs.iit.edu/~iraicu/ Web: http://datasys.cs.iit.edu/ ================================================================= =================================================================